spy

For this example, consider sparseFOContinuous.mat which contains sparse matrices for a continuous-time sparse first-order state-space model.

Extract the sparse matrices from sparseFOContinuous.mat.

load('sparseFOContinuous.mat','A','B','C','D','E');

Create the sparss model object.

sys = sparss(A,B,C,D,E)

Sparse continuous-time state-space model with 1 outputs, 1 inputs, and 199 states.

Use "spy" and "showStateInfo" to inspect model structure. 
Type "help sparssOptions" for available solver options for this model.

The output sys is a continuous-time sparss model object with 199 states, 1 input and 1 output.

You can use the spy command to visualize the sparsity of the sparss model object.

spy(sys)

For this example, consider sparseFODiscrete.mat which contains sparse matrices for a discrete-time sparse first-order state-space model.

Extract the sparse matrices from sparseFODiscrete.mat.

load('sparseFODiscrete.mat','A','B','C','D','E','ts');

Create the sparss model object.

sys = sparss(A,B,C,D,E,ts)

Sparse discrete-time state-space model with 1 outputs, 1 inputs, and 398 states.

Use "spy" and "showStateInfo" to inspect model structure. 
Type "help sparssOptions" for available solver options for this model.

The output sys is a discrete-time sparss model object with 398 states, 1 input and 1 output.

You can use the spy command to visualize the sparsity of the sparss model object.

spy(sys)

You can also view model properties of the sparss model object.

properties('sparss')

Properties for class sparss:

    A
    B
    C
    D
    E
    Offsets
    Scaled
    StateInfo
    SolverOptions
    InternalDelay
    InputDelay
    OutputDelay
    InputName
    InputUnit
    InputGroup
    OutputName
    OutputUnit
    OutputGroup
    Notes
    UserData
    Name
    Ts
    TimeUnit
    SamplingGrid

For this example, consider the sparse matrices for the 3-D beam model subjected to an impulsive point load at its tip in the file sparseBeam.mat.

Extract the sparse matrices from sparseBeam.mat.

load('sparseBeam.mat','M','K','B','F','G','D');

Create the mechss model object by specifying [] for matrix C, since there is no damping.

sys = mechss(M,[],K,B,F,G,D)

Sparse continuous-time second-order model with 3 outputs, 1 inputs, and 3408 degrees of freedom.

Use "spy" and "showStateInfo" to inspect model structure. 
Type "help mechssOptions" for available solver options for this model.

The output sys is a mechss model object containing a 3-by-1 array of sparse models with 3408 degrees of freedom, 1 input, and 3 outputs.

You can use the spy command to visualize the sparsity of the mechss model object.

spy(sys)

For this example, consider the sparse matrices of the discrete system in the file discreteSOSparse.mat.

Load the sparse matrices from discreteSOSparse.mat.

load('discreteSOSparse.mat','M','C','K','B','F','G','D','ts');

Create the discrete-time mechss model object by specifying the sample time ts.

sys = mechss(M,C,K,B,F,G,D,ts)

Sparse discrete-time second-order model with 1 outputs, 1 inputs, and 28408 degrees of freedom.

Use "spy" and "showStateInfo" to inspect model structure. 
Type "help mechssOptions" for available solver options for this model.

The output sys is a discrete-time mechss model object with 28408 degrees of freedom, 1 input, and 1 output.

You can use the spy command to visualize the sparsity pattern of the mechss model object. You can right-click on the plot to select matrices to be displayed.

spy(sys)